






'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


_UpperCamelCase						:						List[str]  =					logging.get_logger(__name__)

_UpperCamelCase						:						str  =					{
    'google/bit-50': 'https://huggingface.co/google/bit-50/resolve/main/config.json',
}


class  snake_case__      (					UpperCamelCase     ,				UpperCamelCase):
					a_        =					"bit"
					a_        =					["preactivation", "bottleneck"]
					a_        =					["SAME", "VALID"]




					def __init__(  self  :		Union[str, Any]				, _A  :		Tuple=3				, _A  :		Dict=64				, _A  :		Any=[2_56, 5_12, 10_24, 20_48]				, _A  :		Optional[int]=[3, 4, 6, 3]				, _A  :		int="preactivation"				, _A  :		Optional[int]="relu"				, _A  :		int=None				, _A  :		Tuple=32				, _A  :		Any=0.0				, _A  :		int=False				, _A  :		Optional[int]=32				, _A  :		List[Any]=1				, _A  :		List[Any]=None				, _A  :		Dict=None				, **_A  :		Union[str, Any]				, )    ->							str:
								super().__init__(**_A      )
								if layer_type not in self.layer_types:
											raise ValueError(F"layer_type={layer_type} is not one of {','.join(self.layer_types      )}"      )
								if global_padding is not None:
											if global_padding.upper() in self.supported_padding:
														UpperCAmelCase_      :       int          =       global_padding.upper()
											else:
														raise ValueError(F"Padding strategy {global_padding} not supported"      )
								UpperCAmelCase_      :       str          =       num_channels
								UpperCAmelCase_      :       List[str]          =       embedding_size
								UpperCAmelCase_      :       Any          =       hidden_sizes
								UpperCAmelCase_      :       Optional[Any]          =       depths
								UpperCAmelCase_      :       List[Any]          =       layer_type
								UpperCAmelCase_      :       List[str]          =       hidden_act
								UpperCAmelCase_      :       Tuple          =       global_padding
								UpperCAmelCase_      :       Optional[int]          =       num_groups
								UpperCAmelCase_      :       List[str]          =       drop_path_rate
								UpperCAmelCase_      :       Any          =       embedding_dynamic_padding
								UpperCAmelCase_      :       Tuple          =       output_stride
								UpperCAmelCase_      :       Union[str, Any]          =       width_factor

								UpperCAmelCase_      :       List[str]          =       ['''stem'''] + [F"stage{idx}" for idx in range(1				, len(_A      ) + 1      )]
								UpperCAmelCase_    ,      UpperCAmelCase_      :       List[Any]          =       get_aligned_output_features_output_indices(
								    out_features=_A				, out_indices=_A				, stage_names=self.stage_names      )










'''simple docstring'''





from __future__ import annotations

import os
from collections.abc import Mapping

_UpperCamelCase						:						Any  =					tuple[int, int]


class  snake_case__      :




					def __init__(  self  :		List[str]				, _A  :		set[int]				, _A  :		Mapping[EdgeT, int]      )    ->							None:
								UpperCAmelCase_      :       set[int]          =       vertices
								UpperCAmelCase_      :       dict[EdgeT, int]          =       {
								    (min(_A      ), max(_A      )): weight for edge, weight in edges.items()
								}




					def 		A      (  self  :		Union[str, Any]				, _A  :		EdgeT				, _A  :		int      )    ->							None:
								self.vertices.add(edge[0]      )
								self.vertices.add(edge[1]      )
								UpperCAmelCase_      :       List[str]          =       weight





					def 		A      (  self  :		str      )    ->							Graph:
								UpperCAmelCase_      :       Graph          =       Graph({min(self.vertices      )}				, {}      )
								UpperCAmelCase_      :       EdgeT
								UpperCAmelCase_      :       int
								UpperCAmelCase_      :       EdgeT
								UpperCAmelCase_      :       int

								while len(subgraph.vertices      ) < len(self.vertices      ):
											UpperCAmelCase_      :       Optional[Any]          =       max(self.edges.values()      ) + 1
											for edge, weight in self.edges.items():
														if (edge[0] in subgraph.vertices) ^ (edge[1] in subgraph.vertices):
																	if weight < min_weight:
																				UpperCAmelCase_      :       Dict          =       edge
																				UpperCAmelCase_      :       Tuple          =       weight

											subgraph.add_edge(_A				, _A      )

								return subgraph






def __UpperCAmelCase   (					A					:			str = "p107_network.txt"		)    ->   int:
			UpperCAmelCase_      :       str          =       os.path.abspath(os.path.dirname(A		)		)
			UpperCAmelCase_      :       str          =       os.path.join(A			,       A		)
			UpperCAmelCase_      :       dict[EdgeT, int]          =       {}
			UpperCAmelCase_      :       list[str]
			UpperCAmelCase_      :       int
			UpperCAmelCase_      :       int

			with open(A		) as f:
						UpperCAmelCase_      :       int          =       f.read().strip().split('''\n'''		)

			UpperCAmelCase_      :       Any          =       [line.split(''','''		) for line in data]

			for edgea in range(1			,       len(A		)		):
						for edgea in range(A		):
									if adjaceny_matrix[edgea][edgea] != "-":
												UpperCAmelCase_      :       Optional[int]          =       int(adjaceny_matrix[edgea][edgea]		)

			UpperCAmelCase_      :       Graph          =       Graph(set(range(len(A		)		)		)			,       A		)

			UpperCAmelCase_      :       Graph          =       graph.prims_algorithm()

			UpperCAmelCase_      :       int          =       sum(graph.edges.values()		)
			UpperCAmelCase_      :       int          =       sum(subgraph.edges.values()		)

			return initial_total - optimal_total


if __name__ == "__main__":
						print(f'''{solution() = }''')


